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Subtomogram averaging from cryo-electron tomograms

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Leigh,  Kendra E.
Sofja Kovalevskaja Group, Max Planck Institute of Biophysics, Max Planck Society;
Buchmann Institute for Molecular Life Sciences, Goethe University of Frankfurt, Frankfurt am Main, Germany;

/persons/resource/persons238643

Chen,  Wenbo
Sofja Kovalevskaja Group, Max Planck Institute of Biophysics, Max Planck Society;
Buchmann Institute for Molecular Life Sciences, Goethe University of Frankfurt, Frankfurt am Main, Germany;

/persons/resource/persons238645

Zhang,  Yingyi
Sofja Kovalevskaja Group, Max Planck Institute of Biophysics, Max Planck Society;
Buchmann Institute for Molecular Life Sciences, Goethe University of Frankfurt, Frankfurt am Main, Germany;

/persons/resource/persons78278

Kudryashev,  Misha       
Sofja Kovalevskaja Group, Max Planck Institute of Biophysics, Max Planck Society;
Buchmann Institute for Molecular Life Sciences, Goethe University of Frankfurt, Frankfurt am Main, Germany;

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Citation

Leigh, K. E., Navarro, P. P., Scaramuzza, S., Chen, W., Zhang, Y., Castaño-Díez, D., et al. (2019). Subtomogram averaging from cryo-electron tomograms. In T. Müller-Reichert (Ed.), Methods in Cell Biology (1, pp. 217-259). Academic Press. doi:10.1016/bs.mcb.2019.04.003.


Cite as: https://hdl.handle.net/21.11116/0000-0004-5BC7-6
Abstract
Cryo-electron tomography (cryo-ET) allows three-dimensional (3D) visualization of frozen-hydrated biological samples, such as protein complexes and cell organelles, in near-native environments at nanometer scale. Protein complexes that are present in multiple copies in a set of tomograms can be extracted, mutually aligned, and averaged to yield a signal-enhanced 3D structure up to sub-nanometer or even near-atomic resolution. This technique, called subtomogram averaging (StA), is powered by improvements in EM hardware and image processing software. Importantly, StA provides unique biological insights into the structure and function of cellular machinery in close-to-native contexts. In this chapter, we describe the principles and key steps of StA. We briefly cover sample preparation and data collection with an emphasis on image processing procedures related to tomographic reconstruction, subtomogram alignment, averaging, and classification. We conclude by summarizing current limitations and future directions of this technique with a focus on high-resolution StA.